Why is the Whales Report Unique?

The Whales Report harnesses knowledge about user behavior from other games and provides developers with crowdsourced intelligence about paying users that would otherwise be hard to come across. A self-published studio might be able to see 100,000 users across two to three titles, but when that data is combined and analyzed from thousands of games, you suddenly have a much more accurate understanding of your users. Traditional analytics and mobile marketing platforms can only show you data that you the developer measured in your game. The Whales Report, as part of the Grow network, redefines this limitation by collecting and analyzing payer insights across many games from different vendors. With user level insights about who will pay and who won’t, your retention and monetization practices can become truly data driven instead of guesswork driven.

Whales Report – Explained

Let’s go over the different parts of the Whales Report with an example:

New paying users: players who are new to your game this week and have paid in the game. You can see how well you are doing at getting more players to pay your game week-over-week.

New paying users graph: this graph shows your historical count of new paying users going 12 weeks back. You can see how well you are doing acquiring payers over time.

New users: players that played your game for the first time during this week. Out of these new users:

Seen in GROW: players that were seen (have played) in the the Grow network before they played your game. Use SOOMLA Insights to know these players better as soon as they enter your game.

Paid in GROW: players that paid before in other games in the Grow network. These are the whales that have entered your game. You should focus your efforts on converting these players to paying users in your game.

Paid in your game: players that have paid exclusively in your game and didn’t pay in other games in the Grow network. If you can raise this metric, then it means you’re doing something right compared to the rest of Grow.

Missed potential sales: this section shows you how well you are doing at converting known whales (those that paid before on Grow) to pay in your game. It shows how many of the whales from Grow that played in your game didn’t pay this week in your game. If a large number of whales came into your game and did not pay, it suggests that you might consider doing something differently to get them to pay in your game as well. Every whale that pays elsewhere and not in your game is practically money that you’ve left on the table. The missed potential sales figure comes from multiplying number of whales not paying in your game with the Weekly ARPPU (= Weekly Average Revenue Per Paying User = Weekly Revenue divided by Weekly Paying Users Count).

Retention: this section shows your payer retention performance over the report’s week days using a cohort analysis chart. The left axis shows the date in which each cohort entered your game and the top shows how many days passed since that entry day. The matching cell for these axis values shows how many payers stayed in your game after this many days since their entry.

Weekly users played: weekly count of users who played your game.

Weekly users paid: weekly count of users who paid in your game.

Weekly conversion: conversion rate for your game this week. Shows what percentage of new users you’ve been able to convert to paying users this week.

All-time users played: total count of users who played your game since you joined the Grow network.

All-time users paid: total count of users who paid in your game since you joined the Grow network.

Average days to payment: how many days on average (on all days since you joined Grow) does it take a paying user to start paying in your game since he started playing it.

Revenue: shows how much revenue you made this week and last week side by side.

Revenue graph: shows your historical revenue over the last 12 weeks.

Tell us what you think

The SOOMLA Whales Report is ever evolving and will continue to grow and offer more insights in the future. We are also diligently working on cleaning up the various figures from fraudulent contribution, so with time you should expect these reports to be even more accurate.

We always love to hear what you think about our products and we are inviting you to suggest new features that can be valuable for you to have in the weekly reports. Feel free to contact me at: onn@soom.la

A server core senior, enthusiastic about quality, creativity and growth. Java-grown, web-enhanced and bash-infused.
Onn holds a B.Sc. in Computer Engineering and an MBA from The Hebrew University of Jerusalem. He used to work for various startup companies in the field of mobile platforms and lately for IBM MobileFirst.

At SOOMLA we aim to give mobile app publishers insights into the revenue they are making from advertising. We specifically help track revenue per user, per segment, per cohort and per traffic source. With the help of this data, we want to help facilitate better monetization and marketing decisions for our clients.